Senior AI Engineer

At Allstate, great things happen when our people work together to protect families and their belongings from life’s uncertainties. And for more than 90 years, our innovative drive has kept us a step ahead of our customers’ evolving needs. From advocating for seat belts, air bags and graduated driving laws, to being an industry leader in pricing sophistication, telematics, and, more recently, device and identity protection.  Job Description We are seeking a Senior AI Engineer on the Enterprise Intelligence Factory team to play a foundational role in building the enterprise Semantic Ontology & Dimension Factory Platform. This platform enables AI‑ready analytics by combining semantic ontologies, knowledge graphs, agentic AI, and data engineering to automatically generate business‑ready star schemas from heterogeneous enterprise data sources. In this role, you will design and implement agent‑driven pipelines that leverage RDF/OWL ontologies, SPARQL, and Large Language Models (LLMs) to perform semantic alignment, dimension mining, and AI‑assisted data modelling at scale. You will work at the intersection of AI, semantics, and modern data platforms, helping establish engineering patterns and best practices for the team. This is a hands‑on, senior individual-contributor role, ideal for engineers who enjoy building core platform capabilities rather than isolated experiments. Key Responsibilities: Design , build, and   maintain   agentic AI pipelines   (using   Google ADK or similar frameworks ) to automate semantic mapping, dimension mining, and   ontology ‑ driven   reasoning.   Create   and evolve   enterprise ontologies   in   RDF/OWL , including upper ontologies and domain extensions aligned to CIM (where applicable), to enable reusable enterprise semantics.   Engineer   LLM ‑ powered   services   for schema understanding, semantic alignment, ontology enrichment, and   AI ‑ assisted   metadata generation, with a focus on accuracy, traceability, and scale.   Implement   SPARQL querying and reasoning layers   over knowledge graphs to drive downstream transformations and ensure consistent interpretation of business concepts.   Architect   and deliver   Python ‑ based   microservices   and batch pipelines that integrate semantic reasoning with modern   data ‑ engineering   workflows.   Build   and   optimize   dimension and fact generation pipelines   on   Microsoft Fabric   (Lakehouse, Spark, SQL, orchestration) to produce   business ‑ ready   star schemas from heterogeneous sources.   Define   and enforce   engineering standards , design patterns, and reusable components for semantic and   AI ‑ driven   data platforms (quality, observability, security, and performance).   Partner   with data architects, domain SMEs, and governance teams to   validate   semantic definitions, manage change, and ensure platform scalability and adoption.   Conduct   code reviews, mentor engineers, and influence technical decisions across the platform to raise engineering quality and delivery velocity.   Required Skills & Qualifications: 6+ years of professional software engineering experience, with   strong   proficiency   in Python   and GenAI .    Hands ‑ on   experience building   LLM ‑ based   systems   using commercial or   open ‑ source   models.    Solid   understanding of   semantic technologies : RDF, OWL, ontologies, knowledge graphs, and   SPARQL .    Experience   designing or working with   agentic AI frameworks   (e.g., Google ADK,   LangChain   agents, or similar).    Strong   background in   data engineering concepts   (ETL/ELT, star schemas,   metadata ‑ driven   pipelines).    Experience   building and operating systems on   cloud platforms , preferably   Microsoft Azure / Microsoft Fabric .    Strong   problem ‑ solving   skills and ability to work in ambiguous, greenfield platform initiatives.   Preferred Skills: Experience   with   enterprise data models   (e.g., CIM or canonical models).    Familiarity   with   semantic alignment, ontology mapping, or data   cataloguing   tools .    Exposure   to   MLOps   /   LLMOps , model evaluation, and AI observability.    Knowledge   of   distributed systems , CI/CD pipelines, and   containerisation .    Experience   building   AI ‑ assisted   analytics or semantic layers   for BI or NLQ use cases.   The hiring manager has flexibility to hire across several levels of seniority. The level will be determined by the selected applicant's skills and competencies. #LI-TE1 Skills Agentic AI, Agentic Design, AI Frameworks, Large Language Models (LLMs), LLM Guardrails, LLM Orchestration, Ontology, Python (Programming Language) Compensation Compensation offered for this role is 100,000.00 - 170,500.00 annually and is based on experience and qualifications. The candidate(s) offered this position will be required to submit to a background investigation. Joining our team isn’t just a job — it’s an opportunity. One that takes your skills and pushes them to the next level. One that encourages you to challenge the status quo. One where you can shape the future of protection while supporting causes that mean the most to you. Joining our team means being part of something bigger – a winning team making a meaningful impact. Allstate generally does not sponsor individuals for employment-based visas for this position. 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